Particle launches Radar to make podcast conversations searchable

In short: Particle has launched Radar, a tool that transcribes and analyzes podcasts so their spoken conversations can be searched and used by other software.

What happened

Particle, a startup known for an AI newsreader app, introduced Radar, a podcast search engine. Radar converts podcast audio into text (like turning a recorded meeting into written notes) and then pulls out key quotes and highlights.

The company says Radar has already transcribed and analyzed more than 130,000 podcasts. It includes the Apple Top 200 podcasts across 135 categories, and Particle says it adds about 20,000 new episodes to its index every day.

Radar also labels different speakers and adds extra details about what is being discussed, such as people, companies, products, and topics. Users can search these conversations on the web, set up alerts when a topic or brand is mentioned, and generate short clips with timestamps so they can jump to the exact moment in an episode.

Particle says some of its highest-volume customers are hedge funds. CEO Sara Beykpour told TechCrunch that hedge funds are directly integrating with Radar through its API (a way for one app to talk to another app, like a restaurant pickup window for software). Other customers include AI search platforms and data resellers, and Particle lists Exa as a partner.

Pricing starts at $29 per month per seat, with a $399 per month business plan that includes 20 seats. API pricing is custom.

Why it matters

Podcasts contain a lot of useful information, but it is hard to find a specific comment without listening. Tools like Radar aim to make audio as easy to search as web pages, which could change how researchers, journalists, and businesses track what people say in public.

Source: TechCrunch AI